​[[{“value”:” Artificial Neural Networks (ANNs) have revolutionized computer vision with great performance, but their “black-box” nature creates significant challenges in domains requiring transparency, accountability, and regulatory compliance. The opacity of these systems hampers their adoption in critical applications where understanding decision-making processes is essential. Scientists… Read More »Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Stereo depth estimation plays a crucial role in computer vision by allowing machines to infer depth from two images. This capability is vital for autonomous driving, robotics, and augmented reality applications. Despite advancements in deep learning, many existing stereo-matching models require domain-specific fine-tuning to… Read More »This AI Paper Introduces FoundationStereo: A Zero-Shot Stereo Matching Model for Robust Depth Estimation Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Modern VLMs struggle with tasks requiring complex visual reasoning, where understanding an image alone is insufficient, and deeper interpretation is needed. While recent advancements in LLMs have significantly improved text-based reasoning, similar progress in the visual domain remains limited. Existing VLMs often fail when… Read More »Groundlight Research Team Released an Open-Source AI Framework that Makes It Easy to Build Visual Reasoning Agents (with GRPO) Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” LLMs are widely used for conversational AI, content generation, and enterprise automation. However, balancing performance with computational efficiency is a key challenge in this field. Many state-of-the-art models require extensive hardware resources, making them impractical for smaller enterprises. The demand for cost-effective AI solutions… Read More »Cohere Released Command A: A 111B Parameter AI Model with 256K Context Length, 23-Language Support, and 50% Cost Reduction for Enterprises Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Normalization layers have become fundamental components of modern neural networks, significantly improving optimization by stabilizing gradient flow, reducing sensitivity to weight initialization, and smoothing the loss landscape. Since the introduction of batch normalization in 2015, various normalization techniques have been developed for different architectures,… Read More »Dynamic Tanh DyT: A Simplified Alternative to Normalization in Transformers Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Like humans, large language models (LLMs) often have differing skills and strengths derived from differences in their architectures and training regimens. However, they struggle to combine specialized expertise across different domains, limiting their problem-solving capabilities compared to humans. Specialized models like MetaMath, WizardMath, and… Read More »SYMBOLIC-MOE: Mixture-of-Experts MoE Framework for Adaptive Instance-Level Mixing of Pre-Trained LLM Experts Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities across various domains, propelling their evolution into multi-modal agents for human assistance. GUI automation agents for PCs face particularly daunting challenges compared to smartphone counterparts. PC environments present significantly more complex interactive elements with dense,… Read More »Meet PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Reasoning capabilities have become essential for LLMs, but analyzing these complex processes poses a significant challenge. While LLMs can generate detailed text reasoning output, the lack of process visualization creates barriers to understanding, evaluating, and improving. This limitation manifests in three critical ways: increased… Read More »Researchers from the University of Cambridge and Monash University Introduce ReasonGraph: A Web-based Platform to Visualize and Analyze LLM Reasoning Processes Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have become crucial in customer support, automated content creation, and data retrieval. However, their effectiveness is often hindered by their inability to follow detailed instructions during multiple interactions consistently. This issue is particularly critical in high-stakes environments, such as financial… Read More »Meet Attentive Reasoning Queries (ARQs): A Structured Approach to Enhancing Large Language Model Instruction Adherence, Decision-Making Accuracy, and Hallucination Prevention in AI-Driven Conversational Systems Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” AI-generated videos from text descriptions or images hold immense potential for content creation, media production, and entertainment. Recent advancements in deep learning, particularly in transformer-based architectures and diffusion models, have propelled this progress. However, training these models remains resource-intensive, requiring large datasets, extensive computing… Read More »HPC-AI Tech Releases Open-Sora 2.0: An Open-Source SOTA-Level Video Generation Model Trained for Just $200K Aswin Ak Artificial Intelligence Category – MarkTechPost